Metal contamination is one of the most challenging environmental problems of the present century. Excessive heavy metals enter into a natural environment to destruct biological diversity and cause harmful influences on an ecological environment and human health. To formulate scientific environmental criteria for metals is a basis of environmental protection and risk assessment. America is a country which internationally develops criteria study first, while an existing criteria system in China mainly copies or draws on foreign achievements and lacks of science. In the latest criteria documents, 15 metals are listed in a directory of precedence-controlled pollutants and non-precedence-controlled pollutants, while only 10 metals have criteria reference values. Water quality criteria values of most of metals are lost, for a primary reason of insufficient biological toxicity data deficiency and a secondary reason of influence by environmental elements. Only criteria research of metals such as copper, nickel is deep. At present, standardized biological toxicity testing is the only way for obtaining a criteria value currently. However, because the heavy metals have wide varieties and complicated structures and forms, manpower, material resources and financial resources need to be consumed during lots of toxicity tests for criteria derivation, and a metal form in a complex biological system is difficult to be accurately measured. Development of heavy metal water quality criteria research is hindered. Although various toxic endpoints are predicted by researchers by virtue of calculation means, a real means for toxicity and water quality criteria prediction is not reported. The development does not depend on a criteria prediction method of testing measurement and conforms to national conditions of China, thereby saving lots of manpower, material resources and financial resources.
A quantitative structure-activity relationship (QSAR) method looks for an inner link between structures and biological activities of targeted pollutants by adopting a statistical analysis means and is widely applied to prediction and evaluation of various toxic effects as an effective means of toxic mechanism researches. The QSAR method is not limited by experimental conditions and testing instruments, and the biological activities of the pollutants are researched and predicted by adopting various computational chemistry and data mining technologies, so the QSAR method has particularly obvious advantages while confronting with batches of pollutants and multiple tested species and has unique charm in aspects of toxicity prediction and risk evaluation. As is known to all, an ionic form is the most active form of metals, and biological activities of dissolved metals are closely related to free ion concentrations. The researchers try to carry out a QSAR research of metal ions in an ideal system and propose a method for predicting the biological activities of the ions based on a quantitative ion characteristic-activity relationship. Newman et al. establish a QSAR equation by utilizing toxicity testing data of marine luminous bacteria (V. fischen) and predict metal toxicity. The result shows that a first hydrolysis constant |log KOH| and the metal ions have a strong interaction relationship on the toxic effects of organisms. Bogaerts et al. indicate that a metal ion soft index σp is an optimal modeling parameter of the toxicity prediction equation while evaluating the interaction relationship between a toxic effect of protozoa (T. pyriformis) and physicochemical characteristics of the metal ions.
The methods above are one-parameter predictive models based on a single species and lack of systematic toxicity prediction and analysis of multiple species in the ecological system, and prediction capabilities and application domains of the models are very limited.
In view of the defects above, the present invention is obtained by the inventor of the present invention through long-term research and practice.